RATE: DOE (C2C OR W2 OR 1099)

We are seeking a highly skilled Artificial Intelligence Engineer to join our dynamic team. This individual will play a critical role in designing, implementing, and maintaining AI-driven applications and infrastructure in a cloud-native environment. This is a hands-on technical position for someone who thrives in a fast-paced, innovative.

REQUIRED SKILLS & EXPERIENCE:

• 5+ years in software development, with expertise in Python .
• Deep experience with AWS serverless components: Lambda, Step Functions, API Gateway (or Lambda Function URLs), DynamoDB, S3.
• Proficient with Docker and Kubernetes (EKS/ECS), cluster scaling, Helm, and K8s manifests.
• Familiarity with MCP spec and LLM frameworks (e.g., Bedrock Agents, LangChain).
• Strong knowledge of IaC tools (Terraform, AWS CDK, or CloudFormation).
• Hands-on with AWS networking and security (VPCs, PrivateLink, IAM policies).
• Experienced in monitoring and logging stacks (CloudWatch, Kibana, Prometheus, Grafana).
• Proven track record in CI/CD pipeline creation and DevOps automation.

SOFT SKILLS:

• Clear and confident communicator—able to work across AI, infra, and security teams.
• Self-starter with a strong sense of ownership and accountability.
• Analytical and methodical in debugging and system design.
• Natural mentor—supports junior team members and promotes best practices.
  Job Type: Contract
  Pay: From $70.00 per hour
  Expected hours: 40 per week

Ability to Commute:

• Charlotte, NC 28277 (Required)

Ability to Relocate:

• Charlotte, NC 28277: Relocate before starting work (Required)

Work Location: In perso

• Design and develop robust software using Python with a focus on RESTful APIs.
• Architect and implement serverless workflows on AWS (Lambda, Step Functions, API Gateway, DynamoDB, S3).
• Deploy and manage containerized applications using Docker and Kubernetes (EKS or ECS); develop Helm charts and scale clusters effectively.
• Implement infrastructure as code (IaC) using Terraform, AWS CDK, or CloudFormation.
• Collaborate on prompt engineering strategies and support tool definition for LLMs.
• Integrate AI/ML tools using Model Context Protocol (MCP) or agent frameworks (e.g., Bedrock Agents, LangChain).
• Apply security best practices including VPC design, PrivateLink, IAM, WAF, and Secrets Manager.
• Build and monitor observability tools including CloudWatch, Prometheus, Grafana, and Kibana.
• Set up and manage CI/CD pipelines using GitHub Actions, AWS CodePipeline, or Azure DevOps.
• Troubleshoot event-driven systems and distributed architectures.
• Mentor junior engineers and promote engineering best practices.